Sequence information includes information elements arranged in a row. For example, a paragraph of text may form a piece of sequence information, and elements of the sequence information are words in the paragraph of text. Currently, sequence information appears in many fields. For example, a user speaks a sentence to a mobile phone and intends the mobile phone to search the spoken sentence. The spoken sentence is sequence information that needs to be converted to text. For another example, a translation program that converts Chinese into English needs to cluster characters together to form words. A designer needs a model to analyze voices and Chinese texts.
To analyze the sequence information, identifying the information elements and the position of each information element, a terminal may perform prediction and analysis on the sequence information by using a model, so as to obtain, the information elements included by the sequence information and the position of each information element. Before the model is used, the model needs to be trained by voices and texts, so that the model can adjust its parameters to increase the accuracy of analysis.
Before performing prediction and analysis on the sequence information by using the training model, the terminal needs to acquire a value of a training parameter and calibrate the training model according to the training parameter to improve accuracy of the model. Therefore, before the training model the training model is calibrated, a technician estimates a training parameter according to experience and inputs the estimated training parameter in the terminal. The terminal receives the training parameter input by the technician and calibrates the training model by using the training parameter.
Having a technician making an estimate highly relies on the experience of the technician and there is no guarantee that the estimate is close to optimal. Therefore, it is desirable to have a method to automatically generate an optimal value of the training parameter.